Three types of statistical time series models have been proposed for the analysis of repeated measurements of blood chemistries or hematologies within an individual. These include a strictly homeostatic model, a nonstationary model which does not presume a homeostatic setpoint, and a more general autoregressive model of which the first two are special cases. All models take into account measurement error in determining the true value at any sampling time. These models are being applied to results from a small sample of presumably normal individuals examined periodically during the last 4 or 5 years. Preliminary results have shown that, as expected, all of these models may be used to describe random changes over time in various commonly measured chemistries and hematologies. In some persons, a substance like serum cholesterol will be controlled with sufficient closeness (even over 4 - 5 years) to be represented by the strictly homeostatic model, whereas the same constituent in other individuals will require a nonstationary model to properly account for variations occurring while the individual remains in a healthy status. BIBLIOGRAPHIC REFERENCES: Harris, E.K.: Some theory of reference values. I. Stratified (categorized) normal ranges and a method for following an individual's clinical reference values. Clin. Chem., 21, 1457, September 1975.